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Visualizing Data & Communicating Results in R with RStudio
Anh Le
Anh Le
Code and run your first R program in minutes without installing anything!
Read more
Code and run your first R program in minutes without installing anything!
Read more
Code and run your first R program in minutes without installing anything!
This course is designed for learners with limited coding experience, providing foundational knowledge of data visualizations and R Markdown. The modules in this course cover different types of visualization models such as bar charts, histograms, and heat maps as well as R Markdown. Completion of the previous course (Data Analysis in R with RStudio & Tidyverse) in this specialization or similar experience is recommended.
To allow for a truly hands-on, self-paced learning experience, this course is video-free.
Assignments contain short explanations with images and runnable code examples with suggested edits to explore code examples further, building a deeper understanding by doing. You’ll benefit from instant feedback from a variety of assessment items along the way, gently progressing from quick understanding checks (multiple choice, fill in the blank, and un-scrambling code blocks) to small, approachable coding exercises that take minutes instead of hours. Finally, a cumulative lab at the end of the course will provide you an opportunity to apply all learned concepts within a real-world context.
Register for this course and see more details by visiting:
OpenCourser.com/course/310knd/visualizing
What's inside
Syllabus
Creating Comparison and Composition Charts
Learn how to create comparison and composition charts.
Creating Distribution Charts
Learn how to create distribution charts.
Read more
Syllabus
Creating Comparison and Composition Charts
Learn how to create comparison and composition charts.
Creating Distribution Charts
Learn how to create distribution charts.
Read more
Creating Specialized Visualizations
Learn how to create specialized visualizations.
Communicating Data Using R Markdown
Learn how to export visualizations as commonly used document files.
Visualizing Data and Communicating Results with R Lab
Given a data set, create a chart that represents that data.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Introduces learners to key data visualization concepts such as bar charts, histograms, and heat maps
Provides a practical and hands-on learning experience with code examples and interactive exercises
Empowers learners to communicate data effectively through R Markdown, allowing for export in various document formats
Assumes prior foundational knowledge in R programming and data analysis, which may limit accessibility for complete beginners
Focuses on basic data visualization principles and does not cover advanced techniques or specialized industry knowledge
Save this course
Save Visualizing Data & Communicating Results in R with RStudio to your list so you can find it easily later:
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Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Visualizing Data & Communicating Results in R with RStudio with these
activities:
Gather a collection of R visualization resources
Show steps
Having a collection of resources will provide you with a valuable reference for future projects.
Browse courses on
R Programming
Show steps
-
Search for online resources on R visualization.
-
Bookmark or save the links to these resources in a central location.
Read 'R Graphics Cookbook'
Show steps
This book provides a comprehensive guide to creating a wide variety of data visualizations using R.
View
R Graphics Cookbook: Practical Recipes for...
on Amazon
Show steps
-
Read through the chapters of the book.
-
Try out the code examples provided in the book.
Complete R exercises
Show steps
Practicing these drills will solidify your understanding of R syntax and data visualization techniques.
Browse courses on
R Programming
Show steps
-
Work through the provided R exercises in the course materials.
-
Attempt to solve additional R exercises found online or in textbooks.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Follow online tutorials on advanced R visualization techniques
Show steps
These tutorials will provide you with additional guidance and insights into more advanced R visualization techniques.
Browse courses on
R Programming
Show steps
-
Search for online tutorials on advanced R visualization techniques.
-
Follow the tutorials and complete the exercises provided.
-
Experiment with the techniques you have learned in your own R projects.
Create a data visualization dashboard
Show steps
Creating a dashboard will allow you to apply your skills in data visualization and R programming to a practical problem.
Browse courses on
Data Visualization
Show steps
-
Identify a dataset that you are interested in visualizing.
-
Design the layout of your dashboard, including the types of charts and graphs you will use.
-
Write the R code to generate the visualizations and arrange them in the dashboard.
-
Deploy your dashboard online or share it with others.
Answer questions and provide guidance on R visualization forums
Show steps
Helping others will reinforce your understanding of R visualization and allow you to connect with other learners.
Browse courses on
R Programming
Show steps
-
Join online forums or communities dedicated to R visualization.
-
Monitor the forums for questions related to R visualization.
-
Provide answers and guidance to those who need it.
Participate in a data visualization competition
Show steps
Participating in a competition will challenge you to push your skills to the limit and learn from others.
Browse courses on
Data Visualization
Show steps
-
Find a data visualization competition that aligns with your interests.
-
Gather and clean the data for your submission.
-
Design and create your data visualization.
-
Submit your visualization to the competition.
Contribute to an open-source R visualization project
Show steps
Contributing to an open-source project will allow you to learn from others, share your knowledge, and make a meaningful contribution to the R community.
Browse courses on
R Programming
Show steps
-
Find an open-source R visualization project that interests you.
-
Review the project's documentation and codebase.
-
Identify an area where you can contribute.
-
Submit a pull request with your contributions.
Gather a collection of R visualization resources
Show steps
Having a collection of resources will provide you with a valuable reference for future projects.
Browse courses on
R Programming
Show steps
Show steps
Show steps
- Search for online resources on R visualization.
- Bookmark or save the links to these resources in a central location.
Read 'R Graphics Cookbook'
Show steps
This book provides a comprehensive guide to creating a wide variety of data visualizations using R.
View
R Graphics Cookbook: Practical Recipes for...
on Amazon
Show steps
Show steps
Show steps
- Read through the chapters of the book.
- Try out the code examples provided in the book.
Complete R exercises
Show steps
Practicing these drills will solidify your understanding of R syntax and data visualization techniques.
Browse courses on
R Programming
Show steps
Show steps
Show steps
- Work through the provided R exercises in the course materials.
- Attempt to solve additional R exercises found online or in textbooks.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Follow online tutorials on advanced R visualization techniques
Show steps
These tutorials will provide you with additional guidance and insights into more advanced R visualization techniques.
Browse courses on
R Programming
Show steps
Show steps
Show steps
- Search for online tutorials on advanced R visualization techniques.
- Follow the tutorials and complete the exercises provided.
- Experiment with the techniques you have learned in your own R projects.
Create a data visualization dashboard
Show steps
Creating a dashboard will allow you to apply your skills in data visualization and R programming to a practical problem.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Identify a dataset that you are interested in visualizing.
- Design the layout of your dashboard, including the types of charts and graphs you will use.
- Write the R code to generate the visualizations and arrange them in the dashboard.
- Deploy your dashboard online or share it with others.
Answer questions and provide guidance on R visualization forums
Show steps
Helping others will reinforce your understanding of R visualization and allow you to connect with other learners.
Browse courses on
R Programming
Show steps
Show steps
Show steps
- Join online forums or communities dedicated to R visualization.
- Monitor the forums for questions related to R visualization.
- Provide answers and guidance to those who need it.
Participate in a data visualization competition
Show steps
Participating in a competition will challenge you to push your skills to the limit and learn from others.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Find a data visualization competition that aligns with your interests.
- Gather and clean the data for your submission.
- Design and create your data visualization.
- Submit your visualization to the competition.
Contribute to an open-source R visualization project
Show steps
Contributing to an open-source project will allow you to learn from others, share your knowledge, and make a meaningful contribution to the R community.
Browse courses on
R Programming
Show steps
Show steps
Show steps
- Find an open-source R visualization project that interests you.
- Review the project's documentation and codebase.
- Identify an area where you can contribute.
- Submit a pull request with your contributions.
Career center
Learners who complete Visualizing Data & Communicating Results in R with RStudio will develop knowledge and skills
that may be useful to these careers:
Data Analyst
Data Analyst
Data analysts are responsible for collecting, cleaning, and analyzing data to help businesses make informed decisions. This course can help you build a foundation in data visualization, which is a key skill for data analysts. You'll learn how to create clear and concise visualizations that communicate data insights effectively.
Data Scientist
Data Scientist
Data scientists use data to solve complex problems and make predictions. This course can help you build a foundation in data visualization, which is a key skill for data scientists. You'll learn how to create visualizations that communicate data insights effectively to both technical and non-technical audiences.
Business Analyst
Business Analyst
Business analysts use data to identify and solve business problems. This course can help you build a foundation in data visualization, which is a key skill for business analysts. You'll learn how to create visualizations that communicate data insights effectively to stakeholders at all levels of an organization.
Statistician
Statistician
Statisticians use data to collect, analyze, interpret, and present information. This course can help you build a foundation in data visualization, which is a key skill for statisticians. You'll learn how to create visualizations that communicate data insights effectively to both technical and non-technical audiences.
Software Engineer
Software Engineer
Software engineers design, develop, and maintain software systems. This course can help you build a foundation in data visualization, which is a key skill for software engineers who work on data-driven applications. You'll learn how to create visualizations that communicate data insights effectively to both technical and non-technical audiences.
Product Manager
Product Manager
Product managers are responsible for managing the development and launch of new products. This course can help you build a foundation in data visualization, which is a key skill for product managers. You'll learn how to create visualizations that communicate data insights effectively to stakeholders at all levels of an organization.
Data Engineer
Data Engineer
Data engineers are responsible for building and maintaining the infrastructure that supports data analysis and data science. This course can help you build a foundation in data visualization, which is a key skill for data engineers. You'll learn how to create visualizations that communicate data insights effectively to both technical and non-technical audiences.
Marketing Analyst
Marketing Analyst
Marketing analysts use data to understand customer behavior and develop marketing campaigns. This course can help you build a foundation in data visualization, which is a key skill for marketing analysts. You'll learn how to create visualizations that communicate data insights effectively to both technical and non-technical audiences.
Operations Research Analyst
Operations Research Analyst
Operations research analysts use data to solve problems in a variety of industries. This course can help you build a foundation in data visualization, which is a key skill for operations research analysts. You'll learn how to create visualizations that communicate data insights effectively to both technical and non-technical audiences.
Financial Analyst
Financial Analyst
Financial analysts use data to make investment recommendations. This course can help you build a foundation in data visualization, which is a key skill for financial analysts. You'll learn how to create visualizations that communicate data insights effectively to both technical and non-technical audiences.
Risk Analyst
Risk Analyst
Risk analysts use data to identify and manage risk. This course can help you build a foundation in data visualization, which is a key skill for risk analysts. You'll learn how to create visualizations that communicate data insights effectively to both technical and non-technical audiences.
User Experience (UX) Designer
User Experience (UX) Designer
User experience (UX) designers use data to improve the user experience of products and services. This course can help you build a foundation in data visualization, which is a key skill for UX designers. You'll learn how to create visualizations that communicate data insights effectively to both technical and non-technical audiences.
Technical Writer
Technical Writer
Technical writers use data to create documentation for products and services. This course can help you build a foundation in data visualization, which is a key skill for technical writers. You'll learn how to create visualizations that communicate data insights effectively to both technical and non-technical audiences.
Information Architect
Information Architect
Information architects use data to design and organize information systems. This course can help you build a foundation in data visualization, which is a key skill for information architects. You'll learn how to create visualizations that communicate data insights effectively to both technical and non-technical audiences.
Librarian
Librarian
Librarians use data to organize and manage information. This course can help you build a foundation in data visualization, which is a key skill for librarians. You'll learn how to create visualizations that communicate data insights effectively to both technical and non-technical audiences.
For more career information including salaries, visit:
OpenCourser.com/course/310knd/visualizing
Reading list
We've selected eight books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Visualizing Data & Communicating Results in R with RStudio.
Save
The official guide to R Markdown, a powerful tool for combining code, markdown, and outputs into dynamic reports and interactive web pages.
A practical guide to creating visually appealing and informative graphs and charts using the ggplot2 package in R.
A practical guide to creating clear and effective data visualizations, emphasizing design principles and best practices.
Save
A classic work on the principles and techniques of data visualization, providing guidance on creating effective and informative charts and graphs.
Save
Covers the principles and best practices for designing effective information dashboards, which are becoming increasingly important for data-driven decision-making.
Helps non-technical professionals create compelling and persuasive data visualizations that communicate insights and drive action.
Save
Provides access to a collection of weekly data visualization challenges, encouraging learners to practice and improve their data visualization skills.
A guide to creating interactive and visually engaging data visualizations for the web, using JavaScript libraries such as D3.js and Observable.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/310knd/visualizing
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Effort
4 weeks of study, 2-3 hours/week
Level
Introductory
Via
Coursera
Institution
Codio
Instructor
Anh Le
Language
English
This course belongs to a
collection
called
Data Science and Analysis Tools - from Jupyter to R Markdown. It's comprised of four courses:
- Data Analysis in R with RStudio & Tidyverse
- Data Analysis in Python with pandas & matplotlib in Spyder
- Visualizing & Communicating Results in Python with Jupyter
- Visualizing Data & Communicating Results in R with RStudio (viewing)
Good to know
Introduces learners to key data visualization concepts such as bar charts, histograms, and heat maps
Provides a practical and hands-on learning experience with code examples and interactive exercises
Empowers learners to communicate data effectively through R Markdown, allowing for export in various document formats
Assumes prior foundational knowledge in R programming and data analysis, which may limit accessibility for complete beginners
Focuses on basic data visualization principles and does not cover advanced techniques or specialized industry knowledge
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